⏱ Quick start
Making a simple line chart with
matplotlib is pretty straightforward thanks to the
If you provide only a series of values, it will consider that these values are ordered and will use values from 1 to n to create the X axis.🔥
For more control on the chart, see the dedicated section below.
# libraries import matplotlib.pyplot as plt import numpy as np # create data values=np.cumsum(np.random.randn(1000,1)) # use the plot function plt.plot(values)
Area charts for timeseries
Area charts are very often used for timeseries visualization. They are particularly adapted when there is only 1 series to display. When several groups must be displayed, they can still be used using faceting.
Line charts for timeseries
Line charts are probably the most common type of viz for timeseries. They are particularly adapted when several groups must be displayed to compare their evolution. But mind the spaghetti plot: too many groups make the figure unreadable.
Heatmap for timeseries
A heatmap can be used to display some temporal data. Here is an example using matplotlib where the evolution of a temperature is displayed over the hour of the day (Y axis) and the day of the year (X axis) organized by month.
candlestick chart is a style of financial chart used to describe price movements. Each "candlestick" typically shows one day, with the Open, High, Low, and Close (OHLC) values for each day.
Here are examples using mplfinance from matplotlib to display the evolution of different prices.
Best python timeseries examples
The first example is a line chart showing how to add labels at the end of each series for better readability. The second shows how to use lollipop to display the evolution of a deviation around a trend. The last one shows how to use an area over a flexible baseline to display the deviation around a historical reference period.